LLM Models
Browse the world's large language models. Compare parameters, benchmarks, VRAM and more.
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0. TL;DR 1. Model Details 2. Training Details 3. Usage 4. Evaluation 5. Citation
Falcon3 family of Open Foundation Models is a set of pretrained and instruct LLMs ranging from 1B to 10B.
OpenCALM is a suite of decoder-only language models pre-trained on Japanese datasets, developed by CyberAgent, Inc.
[!NOTE] Note: " -Paddle " models use PaddlePaddle weights, while " -PT " models use Transformer-style PyTorch weights.
Hy-Embodied-VLM-1.0 Efficient Physical-World Agents Tencent Robotics X × Hy Vision Team × Futian Laboratory
Gemma-2-Llama-Swallow series was built by continual pre-training on the gemma-2 models. Gemma 2 Swallow enhanced the Japanese language capabilities of the original Gemma 2 while retaining the English language capabilities. We use approximately 200 billion tokens that were sampled…
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From Inquiry to Decision: Building Trustworthy Medical AI
We introduce EXAONE 3.5, a collection of instruction-tuned bilingual (English and Korean) generative models ranging from 2.4B to 32B parameters, developed and released by LG AI Research. EXAONE 3.5 language models include: 1) 2.4B model optimized for deployment on small or resour…
SEA-LION is a collection of Large Language Models (LLMs) which has been pretrained and instruct-tuned for the Southeast Asia (SEA) region. The size of the models range from 3 billion to 7 billion parameters. This is the card for SEA-LION-v1-3B.
WangchanLION is a joint effort between VISTEC and AI Singapore to develop a Thai-specific collection of Large Language Models (LLMs), pre-trained for Southeast Asian (SEA) languages, and instruct-tuned specifically for the Thai language.